Towards understanding uncertainty in cloud computing with risks of confidentiality, integrity, and availability

• DOI: 10.1016/j.jocs.2016.11.011
• Publication Date: 2016-11-23T01:23:49Z
• Authors: Andrei Tchernykh; Uwe Schwiegelsohn; El-ghazali Talbi; Mikhail Babenko
• Keywords: Optimization; [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]; Resource provisioning; Uncertainty; 02 engineering and technology; [INFO] Computer Science [cs]; Reliability; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; Privacy; [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]; 0202 electrical engineering, electronic engineering, information engineering; Cloud computing; [INFO]Computer Science [cs]; [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]

An extensive research has led to a general understanding of uncertainty issues in different fields ranging from computational biology to decision making in economics. However, a study of uncertainty on large scale computing systems and cloud computing systems is limited. Most of works examine uncertainty phenomena in users’ perceptions of the qualities, intentions and actions of cloud providers. In this paper, we discuss the role of uncertainty in the resource and service provisioning, privacy, etc. especially, in the presence of the risks of confidentiality, integrity, and availability. We review sources of uncertainty, and fundamental approaches for scheduling under uncertainty. We also discuss potentials of these approaches, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage.